Zusammenfassung
We have developed a spiking neural network simulator, which
is both easy to use and computationally efficient, for the
generation of large-scale computational neuroscience
models. The simulator implements current or conductance based
Izhikevich neuron networks, having spike-timing dependent
plasticity and short-term plasticity. It uses a standard
network construction interface. The simulator allows for
execution on either GPUs or CPUs. The simulator, which is
written in C/C++, allows for both fine grain and coarse
grain specificity of a host of parameters. We demonstrate the
ease of use and computational efficiency of this model by
implementing a large-scale model of cortical areas V1, V4, and
area MT. The complete model, which has 138,240 neurons and
approximately 30 million synapses, runs in real-time on an
off-the-shelf GPU. The simulator source code, as well as the
source code for the cortical model examples is publicly
available.
Nutzer